Night Vision Image Compression Coding And Fusion Processing Based On Wavelet Analysis

Night vision technology is promoted greatly by the needs from the military. The obtainment,transmission and enhancment of night vision image have become the most important researchareas of night vision technology field. In order to improve the night vision image quality andtransmit it effectively, in this dissertation, based on the characteristics of the night visionimage, several algorithms of night vision image compression, enhancement and fusion areproposed. Several research achievements are presented in this dissertation as follows:1. An image evaluating parameter-two dimensional histogram information capacity is proposed in this dissertation. Then the characteristics of low light level image and infrared image are analyzed in detail. This is the theory basis of the night vision image compression, enhancement and fusion algorithm.2. A night vision image compression algorithm based on improved embedded zerotree wavelet is advanced, both the compression ratio and compressed image quality are well considered.3. An algorithm for night vision image enhancement based on dualistic sub-image and two dimensional histogram analysis is brought forward in this dissertation. It can eliminate the drawback of traditional histogram equalization that the fine part is not easy to control and protect. This is meaningful for night vision technology.4. A night vision image fusion algorithm based on wavelet transform is put forward in this dissertation. Two kinds of original images-low light level image and laser assistant vision image, low light level image and infrared image are fused based on the multiresolution contrast of the source images in the wavelet transform domain.5. A modulating fusion algorithm based on wavelet transform is advanced. The low light level image and infrared image are fused using contrast modulating and gray level modulating method.6. A false color night vision image fusion algorithm based on RGB color space is proposed in this dissertation. Low light level bispectral images and infrared images are fused using improved TNO algorithm. It can indeed bring us a natural color image and the object can be recognized more effectively.